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Computation of businesscycle models with the Generalized Schur method

Computation of businesscycle models with the Generalized Schur method The current issue and full text archive of this journal is available at www.emeraldinsight.com/1753-8254.htm Computation of EDUCATION BRIEFING business-cycle models Computation of business-cycle models with the Generalized Schur method 1. Introduction Modern business cycle theory uses stochastic dynamic general equilibrium models in order to explain and forecast the behavior of economic variables such as income, employment, or inflation. In Heer and Maußner (2009), we provide a comprehensive review of both linear and non-linear computational methods in order to solve such models. In most cases, business cycle models are solved with the help of log-linearization around the deterministic steady state. This method is very convenient for at least three reasons: (1) This method is simple, fast, and easy to implement. (2) As shown by Aruoba et al. (2006) and Heer and Maußner (2008), log- linearization often provides for a very accurate approximation, in particular if one is interested in the statistical properties of the economic variables. (3) The solution from this linear method can be used as an initial guess for the computation of a non-linear solution. In general, the complex stochastic dynamic general equilibrium model of the business cycle can be log-linearized around the deterministic steady state resulting in http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Indian Growth and Development Review Emerald Publishing

Computation of businesscycle models with the Generalized Schur method

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1753-8254
DOI
10.1108/17538250910992586
Publisher site
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Abstract

The current issue and full text archive of this journal is available at www.emeraldinsight.com/1753-8254.htm Computation of EDUCATION BRIEFING business-cycle models Computation of business-cycle models with the Generalized Schur method 1. Introduction Modern business cycle theory uses stochastic dynamic general equilibrium models in order to explain and forecast the behavior of economic variables such as income, employment, or inflation. In Heer and Maußner (2009), we provide a comprehensive review of both linear and non-linear computational methods in order to solve such models. In most cases, business cycle models are solved with the help of log-linearization around the deterministic steady state. This method is very convenient for at least three reasons: (1) This method is simple, fast, and easy to implement. (2) As shown by Aruoba et al. (2006) and Heer and Maußner (2008), log- linearization often provides for a very accurate approximation, in particular if one is interested in the statistical properties of the economic variables. (3) The solution from this linear method can be used as an initial guess for the computation of a non-linear solution. In general, the complex stochastic dynamic general equilibrium model of the business cycle can be log-linearized around the deterministic steady state resulting in

Journal

Indian Growth and Development ReviewEmerald Publishing

Published: Sep 25, 2009

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